Influence of 100% and 40% oxygen on penumbral blood flow, oxygen level, and T2*-weighted MRI in a rat stroke model

Accurate imaging of the ischemic penumbra is a prerequisite for acute clinical stroke research. T2* magnetic resonance imaging (MRI) combined with an oxygen challenge (OC) is being developed to detect penumbra based on changes in blood deoxyhemoglobin. However, inducing OC with 100% O2 induces sinus artefacts on human scans and influences cerebral blood flow (CBF), which can affect T2* signal. Therefore, we investigated replacing 100% O2 OC with 40% O2 OC (5 minutes 40% O2 versus 100% O2) and determined the effects on blood pressure (BP), CBF, tissue pO2, and T2* signal change in presumed penumbra in a rat stroke model. Probes implanted into penumbra and contralateral cortex simultaneously recorded pO2 and CBF during 40% O2 (n=6) or 100% O2 (n=8) OC. In a separate MRI study, T2* signal change to 40% O2 (n=6) and 100% O2 (n=5) OC was compared. Oxygen challenge (40% and 100% O2) increased BP by 8.2% and 18.1%, penumbra CBF by 5% and 15%, and penumbra pO2 levels by 80% and 144%, respectively. T2* signal significantly increased by 4.56%±1.61% and 8.65%±3.66% in penumbra compared with 2.98%±1.56% and 2.79%±0.66% in contralateral cortex and 1.09%±0.82% and −0.32%±0.67% in ischemic core, respectively. For diagnostic imaging, 40% O2 OC could provide sufficient T2* signal change to detect penumbra with limited influence in BP and CBF

Heroes and villains of world history across cultures

© 2015 Hanke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedEmergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.This research was supported by grant RG016-P-10 from the Chiang Ching-Kuo Foundation for International Scholarly Exchange (http://www.cckf.org.tw/). Religion Culture Entropy China Democracy Economic histor

Impact of household characteristics on patient outcomes post hip fracture::a Welsh nationwide observational cohort study

BackgroundHip fracture is common in older people and has significant health and care implications. This study aimed to examine the impact of household characteristics (living alone or living with someone who is themselves ill) on adverse outcomes following hip fracture.MethodsA cohort study of hip fracture patients aged ≥50 years living alone or with one co-resident using Welsh nationwide data between January 2013 and December 2018. Outcomes were emergency hospital admission within 30 days and care-home admission and mortality within one year of hospital discharge. Analysis used cause-specific Cox proportional hazards models to examine associations with living alone and with co-resident chronic disease status.ResultsOf the 12,089 hip fracture patients discharged, 56.0% lived alone. Compared to hip fracture patients living with a co-resident, those living alone were more commonly women (78.4% versus 65.2%), older (mean 83.1 versus 78.5 years), and had more long-term conditions (mean 5.7 versus 5.3). In unadjusted analyses, compared to living with a co-resident with 0-1 long-term condition and no dementia, living alone (hazard ratio [HR] 1.44, 95%CI 1.23-1.68), living with someone with dementia (HR 1.57, 95%CI 1.07-2.30), and living with someone with 4+ physical long-term conditions (HR 1.24, 95%CI 1.03-1.49) were associated with an increase in mortality, but no significant association was found in adjusted analysis. Adjusted for age, sex, socioeconomic position, and long-term condition count of the hip fracture patient, living alone (adjusted HR [aHR] 2.26, 95%CI 1.81-2.81) and living with a co-resident with dementia (aHR 2.38, 95%CI 1.59-3.57) were both associated with more than double the risk of care home admission. There were no significant associations with 30-day hospital admission.ConclusionsHip fracture patients who live alone have higher one-year mortality, but associations are explained by the demographic and clinical characteristics of those living alone. However, living alone or living with a co-resident with dementia was independently associated with an additional doubling of the risk of care home admission. Household-based approaches to research and health policy may help target risk groups following hip fracture community discharge and further research is needed to understand the mechanisms by which these associations act

The impact of Place on Multimorbidity:A Systematic Scoping Review

Multimorbidity, commonly defined as the co-existence of two or more long-term conditions, is a major global public health challenge with significant impacts for health and social care systems. There is a substantial body of work identifying different individual- and household-level determinants of multimorbidity, yet the role of place-based characteristics in affecting multimorbidity remains limited. This systematic scoping review identifies place-based risk factors for multimorbidity and further synthesises the potential pathways explaining these relationships using longitudinal evidence. By systematically searching seven major databases, such as Medline, Embase, and Web of Science, using relevant search terms (e.g., MeSH) relating to place-based risk factors and multimorbidity, 76 out of 7,761 studies were included for evidence synthesis. We include studies exploring the relationship between place-based risk factors and multimorbidity among the general population older than 18 years old in the setting of community-dwelling, primary, and secondary care. We identified 12 types of place-based risk factors, with the impacts of area-level deprivation/SES, pollution, and urban/rurality on multimorbidity being most frequently considered and with the most consistent findings, with people living in more deprived/low SES, highly polluted, or more urbanised areas having increased risks of multimorbidity. Further, the impact of these place-based risk factors on multimorbidity varied according to the operationalisation of the multimorbidity measure. We also identified that the impacts of other types of place-based factors on multimorbidity remain underexplored, such as social cohesion and greenspace. Finally, using these longitudinal findings, we propose a conceptual framework linking place and multimorbidity. We suggest that future studies adopt more precise measures of place-level environmental exposures, exploit electronic health records to implement more consistent and reproducible measurements of multimorbidity, moreover, make greater use of longitudinal study designs or analytical approaches better suited to identifying causal processes

Re-visiting Meltsner: Policy Advice Systems and the Multi-Dimensional Nature of Professional Policy Analysis

10.2139/ssrn.15462511-2

Household and area determinants of emergency department attendance and hospitalisation in people with multimorbidity:a systematic review

OBJECTIVES: Multimorbidity is one of the greatest challenges facing healthcare internationally. Emergency department (ED) attendance and hospitalisation rates are higher in people with multimorbidity, but most research focuses on associations with individual characteristics, ignoring household or area mediators of service use. DESIGN: Systematic review reported using the synthesis without meta-analysis framework. DATA SOURCES: Twelve electronic databases (1 January 2000–21 September 2021): MEDLINE/OVID, Embase, Global Health, PsycINFO, ASSIA, CAB Abstracts, Science Citation Index Expanded/ISI Web of Science, Scopus, Cumulative Index to Nursing and Allied Health Literature, Sociological Abstracts, the Cochrane Library, and OpenGrey. ELIGIBILITY CRITERIA: Adults aged ≥16 years, with multimorbidity. Exposure(s) were household and/or area determinants of health. Outcomes were ED attendance and/or hospitalisation. The literature search was limited to publications in English. DATA EXTRACTION AND SYNTHESIS: Independent double screening of titles and abstracts to select relevant full-text studies. Methodological quality was assessed using an adaptation of the Newcastle-Ottawa Quality Assessment Scale tool. Given high study heterogeneity, narrative synthesis was performed. RESULTS: After deduplication, 10 721 titles and abstracts were screened, and 142 full-text articles were reviewed, of which 10 were eligible for inclusion. In people with multimorbidity, household food insecurity was associated with hospitalisation (OR 1.58 (95% CI 1.06 to 2.36) in concordant multimorbidity). People with multimorbidity living in the most versus least deprived areas attended ED more frequently (8.9% (95% CI 8.6 to 9.1) in most versus 6.3% (95% CI 6.1 to 6.6) in least), had higher rates of hospitalisation (26% in most versus 22% in least), and higher probability of hospitalisation (6.4% (95% CI 5.8 to 7.2) in most versus 4.2% (95% CI 3.8 to 4.7) in least). There was non-conclusive evidence that household income is associated with ED attendance and hospitalisation. No statistically significant relationships were found between marital status, living with others with multimorbidity, or rurality with ED attendance or hospitalisation. CONCLUSIONS: There is some evidence that household and area contexts mediate associations of multimorbidity with ED attendance and hospitalisation, but firm conclusions are constrained by the small number of studies published and study design heterogeneity. Further research is required on large population samples using robust analytical methods. PROSPERO REGISTRATION NUMBER: CRD42021283515

“Heroes” and “Villains” of world history across cultures

Emergent properties of global political culture were examined using data from the World History Survey (WHS) involving 6,902 university students in 37 countries evaluating 40 figures from world history. Multidimensional scaling and factor analysis techniques found only limited forms of universality in evaluations across Western, Catholic/Orthodox, Muslim, and Asian country clusters. The highest consensus across cultures involved scientific innovators, with Einstein having the most positive evaluation overall. Peaceful humanitarians like Mother Theresa and Gandhi followed. There was much less cross-cultural consistency in the evaluation of negative figures, led by Hitler, Osama bin Laden, and Saddam Hussein. After more traditional empirical methods (e.g., factor analysis) failed to identify meaningful cross-cultural patterns, Latent Profile Analysis (LPA) was used to identify four global representational profiles: Secular and Religious Idealists were overwhelmingly prevalent in Christian countries, and Political Realists were common in Muslim and Asian countries. We discuss possible consequences and interpretations of these different representational profiles.This research was supported by grant RG016-P-10 from the Chiang Ching-Kuo Foundation for International Scholarly Exchange (http://www.cckf.org.tw/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

The impact of varying the number and selection of conditions on estimated multimorbidity prevalence::a cross-sectional study using a large, primary care population dataset

Background: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. Methods and findings: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of “comorbidity.” Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. Conclusions: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence

Validity of the iPhone M7 motion coprocessor to estimate physical activity during structured and free-living activities in healthy adults

Modern smartphones such as the iPhone contain an integrated accelerometer, which can be used to measure body movement and estimate the volume and intensity of physical activity.  Objectives: The primary objective was to assess the validity of the iPhone to measure step count and energy expenditure during laboratory-based physical activities. A further objective was to compare free-living estimates of physical activity between the iPhone and the ActiGraph GT3X+ accelerometer.  Methods: Twenty healthy adults wore the iPhone 5S and GT3X+ in a waist-mounted pouch during bouts of treadmill walking, jogging, and other physical activities in the laboratory. Step counts were manually counted, and energy expenditure was measured using indirect calorimetry. During two weeks of free-living, participants (n = 17) continuously wore a GT3X+ attached to their waist and were provided with an iPhone 5S to use as they would their own phone.  Results: During treadmill walking, iPhone (703 ± 97 steps) and GT3X+ (675 ± 133 steps) provided accurate measurements of step count compared with the criterion method (700 ± 98 steps). Compared with indirect calorimetry (8 ± 3 kcal·min−1), the iPhone (5 ± 1 kcal·min−1) underestimated energy expenditure with poor agreement. During free-living, the iPhone (7,990 ± 4,673 steps·day−1) recorded a significantly lower (p < .05) daily step count compared with the GT3X+ (9,085 ± 4,647 steps·day−1).  Conclusions: The iPhone accurately estimated step count during controlled laboratory walking but recorded a significantly lower volume of physical activity compared with the GT3X+ during free-living